English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Zero-Inflated Poisson (ZIP) distribution is used to model count data with excessive zeros. In this article, we develop and design an adaptive exponentially weighted moving average (AEWMA) control chart for monitoring ZIP processes. A Markov Chain approach is used to approximate the performance measures; namely the average run length (ARL) and standard deviation of run length (SDRL) of the AEWMA chart. The chart performance is assessed using optimized design parameters that provide the smallest ARL for a range of shifts. A performance comparison of the ZIP-AEWMA chart is conducted with the competing charts in terms of the relative mean index (RMI) metric. Results show that the ZIP-AEWMA chart has superior performance over the competing charts for a wide range of process shifts, especially when the probability of excessive zeros in data is high. The proposed chart is also applied on a real-life application to demonstrate its use. We highly recommend the use of the AEWMA chart for monitoring ZIP processes.

An adaptive EWMA control chart for monitoring zero-inflated Poisson processes